Project Summary/Abstract During sensory experience, the retina transmits a diverse array of visual information to the brain. Neurons along subcortical and cortical pathways must rapidly process the features necessary for navigating through the world. Our goal is to understand how the specificity of long-range cortical connectivity underlies the distribution of visual information to multiple cortical areas, and how these cortical areas subserve context- dependent sensory behaviors. A major hypothesis in visual neuroscience is that sensory information is segregated into parallel streams, in which subpopulations of neurons send axons to cortical areas that are specialized to process distinct visual features. Studies in carnivores and primates have developed this important hypothesis, but many aspects of it remain untested because the tools at hand could not satisfactorily address this question at a cellular level. Recent optical and genetic tools developed for the mouse promise to transform the study of visual cortical function, its relationship to underlying circuitry, and its role in behavior. Our current proposal will establish a mouse model for studying visual microcircuitry across multiple cortical areas and begin to describe rules of functional connectivity between them. We have found that the sensory responses of neurons in the primary visual cortex (V1) of alert mice are tuned to a wide range of spatial and temporal frequencies. This suggests that there is a rich representation of visual experience at the first stage of visual cortical processing. Our preliminary data suggest that two higher visual areas encode reduced and complementary ranges of temporal and spatial frequencies, consistent with a functional organization based on parallel processing. In this grant, we propose to measure this divergence of receptive-fields properties between visual cortical areas (Aim 1), to determine the circuitry underlying this parallel organization (Aim 2), and to assess whether these pathways are differentially modulated by behavior (Aim 3). This work will provide the basis for linking area-specific computations to behaviors-- such as object recognition and navigation-- that rely on the processing of distinct visual features.